Andrew L. Rosenberg, MD; Timothy P. Hofer, MD; Cathy Strachan, MSRN; Charles M. Watts, MD; Rodney A. Hayward, MD
Acknowledgments: The authors thank the members of the University of Michigan Medical Center's Office of Clinical Affairs for collecting the data used in this study and the Consortium for Health Outcomes, Innovation, and Cost Effectiveness Studies (CHOICES) for database support.
Grant Support: Dr. Rosenberg is supported by a grant from the Robert Wood Johnson Foundation and by the Department of Veterans Affairs. Dr. Hofer is supported by a Career Development Grant from the Health Services Research & Development Service of the Department of Veterans Affairs.
Potential Financial Conflicts of Interest: None disclosed.
Requests for Single Reprints: Andrew Rosenberg, MD, Department of Anesthesiology and Critical Care, University of Michigan Medical Center, Room 1G323, Box 0048, Ann Arbor, MI 48109-0048; e-mail, firstname.lastname@example.org.
Current Author Addresses: Dr. Rosenberg: Department of Anesthesiology and Critical Care, University of Michigan Medical Center, Room 1G323, Box 0048, Ann Arbor, MI 48109-0048
Drs. Hofer and Hayward: Ann Arbor Veterans Affairs Health Services Research & Development Service, 3rd Floor, Lobby L, PO Box 130170, Ann Arbor, MI 48113.
Ms. Strachan: Office of Clinical Affairs, University of Michigan Medical Center, 1500 East Medical Center Drive, Ann Arbor, MI 48109.
Dr. Watts: Office of Clinical Affairs, Northwestern Memorial Hospital, 251 East Huron Street, Chicago, IL 60611.
Author Contributions: Conception and design: A.L. Rosenberg.
Analysis and interpretation of the data: A.L. Rosenberg, T.P. Hofer, R.A. Hayward.
Drafting of the article: A.L. Rosenberg, C.M. Watts.
Critical revision of the article for important intellectual content: A.L. Rosenberg, T.P. Hofer, C. Strachan, C.M. Watts, R.A. Hayward.
Final approval of the article: A.L. Rosenberg, T.P. Hofer, R.A. Hayward.
Provision of study materials or patients: C. Strachan.
Statistical expertise: A.L. Rosenberg, T.P. Hofer, R.A. Hayward.
Obtaining of funding: A.L. Rosenberg, C.M. Watts, R.A. Hayward.
Administrative, technical, or logistic support: C. Strachan, C.M. Watts, R.A. Hayward.
Collection and assembly of data: A.L. Rosenberg, C. Strachan.
Common methods of benchmarking clinical performance rarely, if ever, account for admission source and, in particular, the effect of a patient being transferred from one medical center to another. Small biases in comparisons of observed versus expected deaths can substantially affect how high-quality institutions compare with peer hospitals. With the most sophisticated and validated set of case-mix measures available for patients, the intensive care unit is an ideal setting in which to study the effect of a patient's being transferred from another hospital.
To determine the extent of bias in benchmarking outcomes when performance measures do not account for transfer patients' greater severity of illness.
Prospectively developed cohort study.
Medical intensive care unit (MICU) at a tertiary care university hospital.
4579 consecutive admissions for 4208 patients from 1 January 1994 to 1 April 1998.
MICU and hospital lengths of stay, MICU readmission, and hospital mortality rates.
Compared with directly admitted patients, MICU patients transferred from another hospital had significantly higher Acute Physiology Scores at the time of admission and discharge (P = 0.001). Even after full adjustment for case mix and severity of illness, transfer patients had a 38% longer MICU stay (95% CI, 32% to 45%), a 41% longer hospital stay (CI, 34% to 50%), and a 2.2 times greater odds of hospital mortality (CI, 1.7 to 2.8) than directly admitted patients. With identical efficiency and quality, a referral hospital with a 25% MICU transfer rate compared with another with a 0% transfer rate would be penalized by 14 excess deaths per 1000 admissions when a benchmarking program adjusts only for case mix and severity of illness and not for the source of admission.
In a setting with the most thorough diagnostic-based, case-mix adjustment and the most physiologically precise severity-of-illness information, accepting transfer patients can adversely affect efficiency and quality benchmarks. Benchmarking and profiling efforts beyond intensive care units must also recognize and account for this phenomenon; otherwise, referral centers may have an incentive to refuse care for patients who could benefit from being transferred to their facility.
Benchmarking compares performance of providers or systems with a standard. Are such comparisons fair, even if they are adjusted for varying case mix and severity of illness of patients?
This prospective study showed that patients who were transferred to an intensive care unit from other hospitals had worse outcomes than those who were directly admitted. In modeling analyses, benchmarking adjusted with sophisticated case-mix and severity-of-illness information, but not admission source, penalized units with a 25% transfer rate (versus a 0% rate) by 14 excess deaths per 1000 admissions.
Benchmarking of intensive care unit performance should account for transfer patients.
Table 1. Characteristics of Medical Intensive Care Unit Patients Directly Admitted from the Emergency Department or Clinic, Admitted from the General Medicine Floor, or Transferred from Another Hospital
Table 2. Resource Use and Mortality of Medical Intensive Care Unit Patients Directly Admitted from the Emergency Department or Clinic, Admitted from the General Medicine Floor, or Transferred from Another Hospital
Table 3. Intensive Care Unit and Hospital Outcomes for Patients Transferred from Another Hospital to the Medical Intensive Care Unit Compared with Direct and Combined Direct and Floor Intensive Care Unit Admissions, Adjusting for Case Mix and Physiologic Illness Severity
Table 4. Recommendations for Profiling and Research Using Risk-Adjusted Outcome Measures
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Rosenberg AL, Hofer TP, Strachan C, Watts CM, Hayward RA. Accepting Critically Ill Transfer Patients: Adverse Effect on a Referral Center's Outcome and Benchmark Measures. Ann Intern Med. ;138:882–890. doi: 10.7326/0003-4819-138-11-200306030-00009
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Published: Ann Intern Med. 2003;138(11):882-890.
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